Clinical Research Papers:
Survival prediction in patients undergoing radionuclide therapy based on intratumoral somatostatin-receptor heterogeneity
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Rudolf A. Werner1,*, Constantin Lapa1,*, Harun Ilhan2, Takahiro Higuchi1, Andreas K. Buck1, Sebastian Lehner2, Peter Bartenstein2, Frank Bengel3, Imke Schatka4, Dirk O. Muegge5, László Papp6, Norbert Zsótér7, Tobias Große-Ophoff8, Markus Essler8 and Ralph A. Bundschuh8
1 Department of Nuclear Medicine, University Hospital Würzburg, Würzburg, Germany
2 Department of Nuclear Medicine, Ludwig-Maximilians-University Munich, Munich, Germany
3 Department of Nuclear Medicine, Hannover Medical School, Hannover, Germany
4 Department of Nuclear Medicine, Charité - Universitätsmedizin Berlin, Berlin, Germany
5 University of Applied Sciences, Hamburg, Germany
6 Department of Nuclear Medicine, Medical University of Vienna, Vienna, Austria
7 Mediso Medical Imaging Systems Ltd., Budapest, Hungary
8 Department of Nuclear Medicine, University Medical Center Bonn, Bonn, Germany
* These authors have contributed equally to this work
Ralph A. Bundschuh, email:
Keywords: neuroendocrine tumor, tumor heterogeneity, textural parameters, SSTR-PET/CT, radiopeptide therapy
Received: September 20, 2016 Accepted: September 26, 2016 Published: October 02, 2016
The NETTER-1 trial demonstrated significantly improved progression-free survival (PFS) for peptide receptor radionuclide therapy (PRRT) in neuroendocrine tumors (NET) emphasizing the high demand for response prediction in appropriate candidates. In this multicenter study, we aimed to elucidate the prognostic value of tumor heterogeneity as assessed by somatostatin receptor (SSTR)-PET/CT. 141 patients with SSTR-expressing tumors were analyzed obtaining SSTR-PET/CT before PRRT (1-6 cycles, 177Lu somatostatin analog). Using the Interview Fusion Workstation (Mediso), a total of 872 metastases were manually segmented. Conventional PET parameters as well as textural features representing intratumoral heterogeneity were computed. The prognostic ability for PFS and overall survival (OS) were examined. After performing Cox regression, independent parameters were determined by ROC analysis to obtain cut-off values to be used for Kaplan-Meier analysis. Within follow-up (median, 43.1 months), 75 patients showed disease progression (median, 22.2 m) and 54 patients died (median, 27.6 m). Cox analysis identified 8 statistically independent heterogeneity parameters for time-to-progression and time-to-death. Among them, the textural feature Entropy predicted both PFS and OS. Conventional PET parameters failed in response prediction. Imaging-based heterogeneity assessment provides prognostic information in PRRT candidates and outperformed conventional PET parameters. Its implementation in clinical practice can pave the way for individualized patient management.
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